Social Computing

Our research group is focused on conducting research that combines computing and social media behavior. Research has focused on examining the different dimension of the use of social media such as Facebook and Twitter. The research involves a multidisciplinary approach that involves data science, software development, social sciences, communication theory, and psychology. .

 

Social computing refers to the use of computing systems to support of social interactions and behavior. It has become an important concept for use in business It can involve the analysis of social networks, the design of systems to support and facilitate the intentions and goals of social media users, and to explore the discourse and communication evidenced in social media systems such as Facebook, Twitter, blogs, and forums. 

Topics of research include:

  • Personalization of advertising of social media
  • Personality identification and prediction
  • Personalization of social media content for users
  • Age and Gender prediction of social media users
  • Detection of nostalgia in social media
  • Lexicon expansion methodologies
  • Distributed topic modeling

 

The Social Computing Group uses a variety of research approaches: 

  • Empirical studies of users interacting with social computing.
  • Text mining of user generated content such as topic modeling, cluster analysis, sentiment analysis, emotion detection, and personality identification.
  • Building adaptive systems to support user intents and goals during the use of social media.
  • Examination of phenomenon such as emotion propagation through data mining and text mining.
  • Data mining to predict age and gender.

The group often collaborates with researchers at other universities and researchers with a background in such fields as data science, social psychology, economics, design, and communications.

 

Projects: 

None